KR102641735B1 - Ambulatory care support system with diagnostic history management function - Google Patents

Abstract

The system of the present invention includes a server and a medical staff terminal, and the server includes a processor, memory, and a communication module, and the memory includes instructions for causing the processor to perform the following diagnostic steps, The diagnosis steps include, upon receiving animal patient data from the medical staff terminal, selecting chart data matching the animal patient data and transmitting the chart data to the medical staff terminal, and chart input from the medical staff terminal. Upon receiving user input, updating the chart data.

Description

Outpatient treatment support system with diagnosis history management function {AMBULATORY CARE SUPPORT SYSTEM WITH DIAGNOSTIC HISTORY MANAGEMENT FUNCTION}

The present invention relates to an effective re-visit (outpatient treatment) support system through a diagnostic history management function that supports veterinarians to efficiently manage animal patients' medical records when recording treatment for animal patients.

For animal patients with diseases that require multiple outpatient visits, it is important to understand previous treatment history before starting treatment, but in the conventional animal hospital system, it is possible to quickly and efficiently check previous treatment history. There is a difficult problem.

Specifically, in the conventional electronic chart system (EMR), the problem is that the medical records for each session are managed separately, making it difficult for the veterinarian to understand the continuous flow of medical treatment. As a result, the veterinarian must check the medical records one by one. Because a comparison process must be performed, it is difficult to comprehensively understand the animal patient's progress and previous treatment details.

In addition, in the conventional electronic chart system, the veterinarian must manually enter the number of visits for each treatment session and check the animal patient's progress status one by one, so the veterinarian must perform cumbersome tasks and transfer the animal patient. You may make the mistake of missing information about the episode.

In addition, in the conventional electronic chart system, it is difficult for veterinarians to easily check the contents of previous treatment or reflect it in subsequent treatment, and a new chart must be created for each treatment session and an appropriate treatment plan must be established, but the information from the previous treatment session must be established. It is difficult to establish a consistent treatment plan due to the hassle of searching for each treatment individually.

In addition, in the conventional electronic chart system, it is difficult for veterinarians to determine the animal patient's past disease history and whether the disease has been cured. As a result, the veterinarian has to go through the inconvenience of having to manually look up the animal patient's past medical treatment and check whether the animal has been cured. I'm going through it.

In order to solve these problems, a veterinary hospital management system that effectively supports return visits is needed, through efficient management of medical records, ensuring smooth information sharing, providing consistent medical records, and accurate tracking of vaccination and treatment schedules, etc. A method is needed to realize this.

Meanwhile, the matters described as background technology above are only for the purpose of improving understanding of the background of the present application, and should not be taken as an acknowledgment that they correspond to prior art already known to those skilled in the art. .

Public Patent Publication No. 10-2019-0135691, 2019.12.09.

In order to solve the above-mentioned problems, our hospital is an integrated animal hospital electronic chart system to manage data from continuous treatment, automatically creates and manages medical records for each treatment session, and allows veterinarians to make a diagnosis. The progress of the diagnosis and the number of re-visits can be automatically recorded each time, helping veterinarians easily understand the patient's progress, and deciding which disease to focus on when opening the treatment chart. The purpose is to provide a system that supports this.

In addition, unlike conventional electronic chart systems, our hospital automatically reflects diseases requiring repeat visits in the chart to create a history and automatically increases the number of visits, eliminating the inconvenience of veterinarians having to manually enter the number of visits for each treatment session. The purpose is to provide a system that accurately maintains the treatment history of animal patients while resolving the problem.

In addition, our hospital can record the diseases suffered in the past and whether the disease has been cured. Accordingly, the veterinarian can identify the disease status of the animal patient by specifying whether the disease has been cured in the treatment chart. The purpose is to provide a system to support animal patients' guardians and veterinarians to focus on disease treatment by managing data to continue treatment until the disease is completely cured.

In addition, in order to maintain consistency of treatment plan in consecutive treatment, our hospital automatically checks previous treatment contents and reflects this to provide treatment history to establish a consistent treatment plan. In addition, the veterinarian provides treatment history to establish a consistent treatment plan. The purpose is to provide a system that increases the effectiveness of treatment for animal patients by making it easy to find the treatment details of each treatment session.

The problems that the present application seeks to solve are not limited to the problems mentioned above, and other problems not mentioned can be clearly understood by those skilled in the art from the description below.

In the system according to various embodiments of the present application, it includes a server and a medical staff terminal, wherein the server includes a processor, memory, and a communication module, and the memory allows the processor to perform the following diagnostic steps. It includes commands, and the diagnostic steps include, upon receiving animal patient data from the medical staff terminal, selecting chart data matching the animal patient data and transmitting the chart data to the medical staff terminal, and the medical staff terminal. Upon receiving a user input for chart input from the user, updating the chart data, wherein the chart data includes at least one of the name of the veterinarian in charge, animal information, diagnosis history information, prescription history information, and treatment history information. Includes.

The diagnostic steps according to various embodiments of the present application include, in updating the chart data, receiving at least one diagnosis for a condition from the medical staff terminal, and determining whether to reexamine the diagnosis based on the chart data. A determining step, when it is determined that the diagnosis is the first examination, a user input of selecting at least one of a check button for confirmation of the diagnosis and a check button for termination of the disease, and the diagnosis by the veterinarian who made the diagnosis Receiving diagnostic data including information, and updating a history of the diagnosis name in the chart data based on the diagnostic data, wherein the diagnostic data includes disease information, test information, symptom information, It may include at least one of prescription information and information on the diagnostician.

The diagnostic steps according to various embodiments of the present application include, when it is determined that the diagnosis is a repeat diagnosis, at least one second treatment included in the unfinished medical history that matches the same diagnosis as the diagnosis, based on the chart data. Selecting diagnostic data, identifying a return visit for the diagnosis based on the second diagnosis data, and the second diagnosis data, a veterinarian name matched to the second diagnosis data, and the return visit number. It may include transmitting visitation history data for to the medical staff terminal.

The diagnosis steps according to various embodiments of the present application include, upon receiving a user input for selecting at least one second condition matched to the visit history data from the medical staff terminal, selecting the second condition among the second diagnosis data. It may include selecting matching third diagnostic data, and transmitting the third diagnostic data to the medical staff terminal.

The diagnosis steps according to various embodiments of the present application include, when updating the history, if it is determined that the diagnosis is a repeat diagnosis, matching and storing the number of times the diagnosis was repeated, based on the diagnosis data, If the diagnosis is identified as confirmed, storing the diagnosis as a confirmed diagnosis, and if the diagnosis is not identified as confirmed, storing the diagnosis as a probable diagnosis, and based on the diagnosis data, the condition is terminated. If it is identified as being treated, it may include the step of classifying the diagnosis as a condition for which treatment has been completed.

The system according to various embodiments of the present application includes a reception terminal,

The memory includes instructions for causing the processor to perform the following acceptance steps, which include receiving the animal patient data and the acceptance data from the reception terminal, and the chart matching the animal patient data. Selecting data, selecting the medical staff terminal based on the chart data and the reception data, transmitting schedule data of the medical staff terminal to the reception terminal, and transmitting the schedule data from the reception terminal When receiving a user input for selecting, transmitting the animal patient data and the reception data to the medical staff terminal, wherein the reception data includes information about the symptoms of the animal patient and changes in the animal patient's weight. It may include at least one of information, information about the visit time of the animal patient, and the name of a veterinarian designated by the guardian of the animal patient.

The memory includes instructions for causing the processor to perform the following schedule management steps, which include, when the chart data is updated, identifying reservation data based on the updated chart data; Based on the reservation data, identifying at least one reservation item among a reservation for a visit, a reservation for hospitalization, and a call reservation, and updating the schedule data based on the reservation item. there is.

The memory according to various embodiments of the present application includes data on the species of the animal, data on the age of the animal, data on the sex of the animal, data on medical treatment history, diagnostic data, number of visits for each disease, and data for each disease. An artificial intelligence model that is trained to receive data on the condition and data on the animal is input by learning data including at least one of the number of times it has been terminated and output at least one veterinarian name is stored, and the reception steps include: In selecting the medical staff terminal, inputting the animal patient data and the reception data into the artificial intelligence model, identifying at least one second medical staff terminal according to the output of the artificial intelligence model, and the animal It may include selecting the medical staff terminal based on information about the patient's visit time and schedule data for each of the second medical staff terminals.

The reception steps according to various embodiments of the present application include, in identifying the second medical staff terminal, at least one device matching at least one of the animal patient data and the reception data, based on the output of the artificial intelligence model. 1 Identifying the primary ranking of veterinarians, if at least one second veterinarian among the first veterinarians is identified that matches the animal patient data for a critical period, the number of times it matches the animal patient data for the critical period Calculating a secondary ranking of the first veterinarian by applying a first weight proportional to the primary ranking of the second veterinarian, wherein, among the first veterinarians, a third that matches the intake data for a threshold period When at least one veterinarian is identified, calculating a second weight proportional to the number of generated medical data of the third veterinarian accumulated over a critical period, proportional to the number of generated medical data of the third veterinarian accumulated outside of the critical period. However, calculating a third weight, wherein the proportional value has a smaller value than the proportional value of the second weight, applying the second weight and the third weight to the third ranking of the third veterinarian, It may include calculating the tertiary rank of the first veterinarian, and identifying the second medical staff terminal of each fourth veterinarian located within a certain rank based on the tertiary rank of the first veterinarian.

Other specific details herein are included in the detailed description and drawings.

1 is a system configuration diagram according to an embodiment of the present application.
Figure 2 is a server configuration diagram according to an embodiment of the present application.
Figure 3 is a basic flowchart of the diagnosis step according to an embodiment of the present application.
4 to 10 illustrate display screens of a medical staff terminal according to an embodiment of the present invention.
The above drawings are provided as examples so that the idea of the present application can be sufficiently conveyed to those skilled in the art.
Accordingly, the present application is not limited to the drawings presented below and may be embodied in other forms.
Additionally, like reference numerals refer to like elements throughout the specification.
In addition, it should be noted that in the above drawings, to facilitate understanding, certain parts are enlarged or reduced not in proportion to the scale.

Various embodiments are now described with reference to the drawings. In this specification, various descriptions are presented to provide a better understanding of the disclosure. However, it is clear that these embodiments may be practiced without these specific descriptions.

As used herein, the terms “component,” “module,” “system,” and the like refer to a computer-related entity, hardware, firmware, software, a combination of software and hardware, or an implementation of software. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, a thread of execution, a program, and/or a computer. For example, both an application running on an electronic device and the electronic device can be a component. One or more components may reside within a processor and/or thread of execution. A component may be localized within one computer. A component may be distributed between two or more computers. Additionally, these components can execute from various computer-readable media having various data structures stored thereon. Components can transmit signals, for example, with one or more data packets (e.g., data and/or signals from one component interacting with other components in a local system, a distributed system, to other systems and over a network such as the Internet). Depending on the data being transmitted, they may communicate through local and/or remote processes.

Additionally, the term “or” is intended to mean an inclusive “or” and not an exclusive “or.” That is, unless otherwise specified or clear from context, “X utilizes A or B” is intended to mean one of the natural implicit substitutions. That is, either X uses A; X uses B; Or, if X uses both A and B, “X uses A or B” can apply to either of these cases. Additionally, the term “and/or” as used herein should be understood to refer to and include all possible combinations of one or more of the related listed items.

Additionally, the terms “comprise” and/or “comprising” should be understood to mean that the corresponding feature and/or element is present. However, the terms “comprise” and/or “comprising” should be understood as not excluding the presence or addition of one or more other features, elements and/or groups thereof. Additionally, unless otherwise specified or the context is clear to indicate a singular form, the singular terms herein and in the claims should generally be construed to mean “one or more.”

And, the term “at least one of A or B” should be interpreted to mean “a case containing only A,” “a case containing only B,” and “a case of combining A and B.”

Those skilled in the art will additionally recognize that the various illustrative logical blocks, components, modules, circuits, means, logic, and algorithm steps described in connection with the embodiments disclosed herein may be implemented using electronic hardware, computer software, or a combination of both. It must be recognized that it can be implemented with To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented in hardware or software will depend on the specific application and design constraints imposed on the overall system. A skilled technician can implement the described functionality in a variety of ways for each specific application. However, such implementation decisions should not be construed as causing a departure from the scope of the present disclosure.

The description of the presented embodiments is provided to enable anyone skilled in the art to use or practice the present application. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Therefore, the present application is not limited to the embodiments presented herein. This disclosure is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

Network function, artificial neural network, and neural network may be used interchangeably herein.

Various embodiments described herein can be implemented, for example, in recording and storage media readable by a computer or similar device using software, hardware, or a combination thereof.

According to hardware implementation, the embodiments described herein include application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), and field programmable gate arrays (FPGAs). It may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and other electrical units for performing functions. In some cases, as described herein, The described embodiments may be implemented in the processor itself of the electronic device.

Figure 1 is a system configuration diagram according to an embodiment of the present application, and Figure 2 is a server configuration diagram according to an embodiment of the present application.

As shown in FIG. 1, systems according to various embodiments of the present application include a server and a medical staff terminal, and as shown in FIG. 2, the server includes a processor, memory, and a communication module.

The configuration of the server shown in Figure 2 is only a simplified example. In one embodiment of the disclosure, a server may include different configurations for performing the computing environment of the server, and only some of the disclosed configurations may constitute the server.

The server may include a processor, memory, and communication modules.

The processor may be composed of one or more cores, such as the server's central processing unit (CPU: Central Processing Unit), and the general purpose graphics processing unit (GPGPU: General Purpose Graphics Processing Unit). ), Tensor Processing Unit (TPU), etc. It may include a processor for data analysis and deep learning. The processor can read the computer program stored in the memory and perform data processing for machine learning according to the embodiments of the present application. Additionally, the processor controls the configuration of the server to operate and can implement overall system operation.

For example, a processor can typically control the overall operation of a server. The processor can provide or process appropriate information or functions to the user by processing signals, data, information, etc. input or output through the components discussed above, or by running an application program stored in memory.

Additionally, the processor may control at least some of the components of the server to run the application program stored in the memory. Furthermore, the processor may operate in combination with at least two or more of the components included in the server to run the application program.

According to one embodiment of the present application, a processor may perform operations for learning a neural network. The processor processes input data for learning in deep learning (DL), extracts features from the input data, calculates errors, updates weights of the neural network using backpropagation, etc. Perform calculations for learning of neural network can do. At least one of the processor's CPU, GPGPU, and TPU is capable of processing learning of the network function. For example, CPU and GPGPU can work together to process learning of network functions and data classification using network functions.

The medical staff terminal may include various electronic devices such as the user's mobile terminal, laptop, or desktop.

The medical staff terminal may be comprised of a second processor, a second memory, a second communication module, and a display. Since the description of the second processor, second memory, and second communication module is detailed in FIG. 2, it will be omitted. The display may include a variety of displays and may include a touch screen display.

Figure 3 is a basic flowchart of the diagnosis step according to an embodiment of the present invention, and Figures 4 to 10 show a display screen of a medical staff terminal according to an embodiment of the present invention.

The following is a description of the configuration of the UI (User Interface) of the application provided according to the embodiment of the present application.

The UI of this hospital, which will be described later, is based on what is displayed through the medical staff terminal 200, but is not limited to this.

As shown in Figure 4, which constitutes the UI provided by this hospital, information on the animal patient is displayed in area a1, the patient diagnosis chart, which is the diagnosis history of the animal patient, is displayed in area a2, and area a3 displays today's treatment information. This is an area where a chart according to can be entered, and may be an area where the contents of the questionnaire and findings are recorded.

In addition, the a4 area that makes up the UI is an area that records the animal patient's condition and diagnosis, and the a5 area is a veterinarian's prescription (ex. medication, injection, etc.) and examination (ex. blood test, etc.) based on the animal patient's condition. This is an area to record and directly perform (image examination, etc.) or request the recorded information, and the a6 area is a request button for sending guidance data, a care guide, and may be an entry button for sending guidance data to the guardian's terminal.

Additionally, the a7 area constituting the UI is an area that manages the diagnosis history of animal patients, and the history of multiple diagnosis data can be displayed.

In addition, the UI includes an area for entering notes, an area for recording vitals, a search box for searching the name of an animal or guardian, and can further include buttons to enter categories such as schedule, medical expenses, and inpatient management. and is not limited to this.

As shown in FIG. 5, when inputting the a4 area, the server 100 selects data matching the keyword entered in the a4 area from the Korean name for the disease, the English name for the disease, and the EMR (electronic chart). Contains code connection points that refer to the disease, explanations to help you understand the disease, guidance on general treatment methods for the disease, tips for guardians to manage the disease, and precautions for managing the disease. Explanations of important items on already registered disease notices can be provided through the application.

In addition, as shown in Figure 6, the a4 area displays the disease system classification and diagnosis name for each condition, a check box (a4-1) for checking the confirmed status for each condition, and the termination status. It may include a check box (a4-2) to check, display the veterinarian who performed the diagnosis, and include a button to receive input for deleting the record for each condition.

Meanwhile, as shown in FIG. 7, the a7 area includes a7-1, a button that displays only the unchecked diagnostic data for a4-2 in FIG. 6 among the diagnostic data constituting the chart data. Each diagnostic data includes keywords such as the system classification in Figure 6, diagnosis name, and name of the veterinarian who created the diagnostic data, and tags (tag 1, tag 2, tag 3) indicating the medical treatment company for the disease. And, for each piece of diagnostic data, the date of diagnosis, treatment progress status (e.g. in progress, start of re-examination, preliminary diagnosis, confirmed diagnosis, treatment completed), and date of completion of cure can be displayed.

Here, the preliminary diagnosis may be displayed for diagnostic data in which the check box (a4-1) for checking the confirmed status is unchecked.

At this time, when the veterinarian selects each tag displayed in the a7 area, our system searches the animal patient's medical treatment data related to the keyword indicated in the tag and displays a result window for the search results, as shown in FIG. 9. It can be displayed.

Specifically, upon receiving a user input selecting tag 1 for the keywords 'Digestive System|Diarrhea, Acute Diarrhea, Acute' through the medical staff terminal, the server displays the digestive system chart view, and 'Diarrhea, Acute Diarrhea, Acute' The a7-2 window that receives the selection for any one of the result windows pops up, and when the selection for 'Diarrhea, Acute Diarrhea, Acute' is received, for the diagnosis, keywords related to 'Diarrhea, Acute Diarrhea, Acute' A search window for selecting items may be displayed, and a result window in which diagnostic data is displayed, as shown in FIG. 10, may be displayed as a search result for at least one keyword checked in a check box according to user input.

Meanwhile, as shown in FIG. 8, area a7 includes a check box (a4-3) for checking whether to repeat the examination when any one diagnostic data is selected, matching each diagnostic data, and entering area a4. A visitation recording window may be displayed, including a visitation start button (a3-2) for obtaining input.

By configuring this UI, our system provides improved treatment efficiency to veterinarians in continuously managing treatment, maximizes the treatment effect of animal patients by automatically managing re-visit times and recording whether or not the disease has been cured, and can be used by different veterinarians. When treating a single animal patient, cooperation between medical staff can be strengthened and the animal patient's treatment experience can be improved.

Specifically, according to our system, by automatically recording the progress of the disease and the number of re-visits in the medical chart, veterinarians can easily determine the progress of the animal patient's disease and identify which diseases should be mainly seen in today's treatment. In addition, through the history of diseases suffered in the past, it is easy to check whether the disease suffered in the past has been cured, so that a treatment plan can be efficiently established and the patient can focus on treatment.

In addition, according to our system, veterinarians can identify the number of times an animal patient has been revisited through history using just a tag matched to the most recent diagnostic data. Accordingly, treatment can be performed according to the progress of the diagnosis, and past Depending on whether the disease suffered from the patient is cured, the continuity and effectiveness of the treatment can be confirmed. Through this, the treatment process of the animal patient can be continued effectively and specialized treatment can be provided for each animal patient.

In addition, according to our system, medical records can be shared between medical staff, allowing for the exchange of feedback. Through this, various opinions and knowledge can be shared, effective treatment methods can be derived, and effective medical services can be provided to animal patients. can be provided.

In addition, according to our system, veterinarians can easily view previous treatment details and establish treatment plans based on this, thereby improving understanding of each animal patient and facilitating communication with the animal patient's guardian. It is maintained properly and treatment tailored to the individual needs and circumstances of the animal patient's guardian can be provided to the animal patient, helping to increase the satisfaction of each animal patient and the animal patient's guardian and trust in the veterinarian.

The memory contains instructions for causing the processor to perform the following diagnostic steps.

Specifically, as shown in FIG. 3, when the server performs diagnostic steps, when the server receives animal patient data from the medical staff terminal, it selects chart data matching the animal patient data and transmits the chart data to the medical staff terminal. It is transmitted to (S310), and when user input for chart input is received from the medical staff terminal, the chart data is updated (S320).

Chart data includes the name of the veterinarian in charge, animal information (ex. species, age, gender, etc.), diagnosis history information (ex. medical records such as underlying diseases, diseases suffered, allergies, etc.), prescription history information (ex. information taken) Includes at least one of the following: medication, medication being taken, etc.), and treatment history information (e.g., type of test administered, etc.).

At this time, in step S320, when the server receives at least one diagnosis for the condition from the medical staff terminal, it can determine whether to revisit the diagnosis based on chart data.

If it is determined that this is the first diagnosis for the diagnosis, the server includes a user input for selecting at least one of a check button for confirmation of the diagnosis and a check button for termination of the condition, and information on the diagnosing person, the veterinarian who made the diagnosis. Diagnostic data can be received.

Afterwards, the server may update the history of the diagnosis name of the chart data based on the diagnosis data, and the plurality of diagnosis data included in the chart data are each listed based on the date and time of occurrence of the diagnosis data, and indicate the ongoing disease. First, it can be exposed to a veterinarian through a medical staff terminal.

Diagnosis data includes disease information (ex. diagnosis name for the condition), test information (ex. type of test performed), symptom information (ex. conditions such as digestive problems, vomiting, diarrhea, etc.), prescription information (ex. prescribed medication) , and information on the diagnosing person (ex. name of veterinarian in charge, name of pharmacist in charge, etc.).

On the other hand, if it is determined that the diagnosis is a repeat diagnosis, the server may select at least one second diagnosis data included in the unfinished medical treatment history that matches the same diagnosis based on the chart data.

Thereafter, the server identifies the re-visit round for the diagnosis based on the second diagnosis data, and sends the second diagnosis data, the name of the veterinarian in charge matched to the second diagnosis data, and the re-visit history data for the re-visit round to the medical staff terminal. Can be transmitted.

At this time, when receiving a user input for selecting at least one second condition that matches the visit history data from the medical staff terminal, the server selects third diagnosis data that matches the second condition from the second diagnosis data, and the medical staff Third diagnostic data can be transmitted to the terminal.

Meanwhile, if it is determined that the diagnosis is a repeat diagnosis, when updating the history, the server may match and store the number of times the patient was re-diagnosed with the diagnosis.

Accordingly, based on the diagnosis data, if the diagnosis is identified as confirmed, the server may store the diagnosis as confirmed. If the diagnosis is not identified as confirmed, the server may store the diagnosis as a probable diagnosis.

Thereafter, if the server identifies the condition as terminated based on the diagnosis data, it may classify the diagnosis as a condition for which treatment has been completed in the history of the animal patient.

Meanwhile, the memory may include instructions for the processor to perform the following acceptance steps.

Accordingly, when the server performs the reception steps, the server may receive animal patient data and reception data from the reception terminal, and select chart data matching the animal patient data.

The server may select a medical staff terminal based on the chart data and reception data, and transmit certain data of the medical staff terminal to the reception terminal.

Thereafter, upon receiving a user input for selecting certain data from the reception terminal, the server may transmit the animal patient data and reception data to the medical staff terminal.

At this time, the reception data includes information on the animal patient's symptoms, information on the animal patient's weight change, and information on the animal patient's visit time (ex. If the animal patient has already visited the hospital, the time when treatment was received, the animal patient If a visit to the hospital is scheduled, it may include at least one of the scheduled time), and the name of the veterinarian designated by the animal patient's guardian.

Meanwhile, the memory according to various embodiments of the present application includes data on the species of the animal, data on the age of the animal, data on the gender of the animal, data on medical treatment history, diagnostic data, number of visits for each condition, and disease An artificial intelligence model trained to receive data on the condition and data on the animal and output at least one veterinarian name may be stored by learning data including at least one of the number of star terminations.

Accordingly, when the server selects a medical staff terminal based on chart data and reception data, animal patient data and reception data can be input into the artificial intelligence model.

Thereafter, the server identifies at least one second medical staff terminal according to the output of the artificial intelligence model, and selects the medical staff terminal based on information about the visit time of the animal patient and schedule data of each second medical staff terminal, Among the veterinarians with a high level of relevance in relation to the animal patient's current condition, a veterinarian who can make reservations or currently provide treatment according to the schedule can be designated as the veterinarian in charge of the animal patient.

Meanwhile, in identifying the second medical staff terminal, the server may identify the primary ranking of at least one first veterinarian matching at least one of animal patient data and reception data, based on the output of the artificial intelligence model. there is.

Among the first veterinarians, if at least one second veterinarian is identified that matches the animal patient data for the critical period, the server assigns a first weight proportional to the number of matches to the animal patient data for the critical period to the second veterinarian. By applying this to the first ranking, the second ranking of the first veterinarian can be calculated.

Thereafter, if at least one third veterinarian among the first veterinarians is identified that matches the reception data for the critical period, the server applies a second weight proportional to the number of times the third veterinarian's treatment data has been generated accumulated for the critical period. It can be calculated.

Accordingly, the server calculates a third weight, which is proportional to the number of times the third veterinarian's medical data is generated accumulated outside of the critical period, but has a proportional value smaller than the proportional value of the second weight, and the third veterinarian's 2 By applying the second weight and the third weight to the primary ranking, the tertiary ranking of the first veterinarian can be calculated.

Accordingly, the server may identify the second medical staff terminal of each of the fourth veterinarians located within a certain rank based on the third rank of the first veterinarian.

Accordingly, the server performs an operation to increase the ranking by considering the second veterinarian who recently performed treatment for the animal patient in question and the third veterinarian who recently performed treatment for diseases similar to those of the animal patient requesting treatment. In particular, for third-party veterinarians, different standards for the number of recent and previous consultations are applied to raise the ranking of third-party veterinarians who have recently been highly active, so that a veterinarian suitable for the condition of the animal patient in question is selected. can be recommended.

As an example, in calculating the second ranking and the third ranking, the output of the artificial intelligence model is, for each group with the same animal species, animal age, animal sex, and underlying disease, the corresponding animal patient In the case of a score for each veterinarian, calculated to be inversely proportional to the time taken to cure a similar disease that matches the condition of the corresponding animal patient in the matching group, and to be proportional to the number of cures for the similar disease for each group, the server 2 A secondary ranking of all veterinarians, that is, the first veterinarian, can be calculated by applying the first weight to the veterinarian's score.

The server may then apply the first weight and the second weight to the third veterinarian's score to calculate a third ranking based on the second ranking.

In another embodiment, in calculating the first ranking, the output of the artificial intelligence model is the number of similar diseases for each veterinarian calculated for each group with the same animal species, animal age, animal sex, and underlying disease. In the case of the number of treatments and the number of cures for similar diseases by veterinarian, the server identifies the first value, which is the number of cures of animals that received treatment within a critical period for each group of the first veterinarian, and matches the first value of the first veterinarian to the first value. A second value, which is the average number of treatments for each matched group, can be calculated.

Accordingly, the server calculates a first score that is proportional to the first value and a second score that is inversely proportional to the second value, calculates a total score by adding the first score to the second score, and uses the total score as the basis. The first ranking can be calculated.

Meanwhile, the memory may include instructions for the processor to perform the following schedule management steps.

Accordingly, when the server performs schedule management steps and the chart data is updated, the server may identify reservation data based on the updated chart data.

Thereafter, the server may identify at least one reservation item among a reservation for a visit to a hospital, a reservation for a hospitalization, and a call reservation based on the reservation data, and update the schedule data based on the reservation item.

Those of skill in the art will understand that the various illustrative logical blocks, modules, processors, means, circuits and algorithm steps described in connection with the embodiments disclosed herein may be used in electronic hardware, (for convenience) It will be understood that the implementation may be implemented by various forms of program or design code (referred to herein as software) or a combination of both. To clearly illustrate this interoperability of hardware and software, various illustrative components, blocks, modules, circuits and steps have been described above generally with respect to their functionality. Whether this functionality is implemented as hardware or software depends on the specific application and design constraints imposed on the overall system. A person skilled in the art may implement the described functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the present application.

The various embodiments presented herein may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques. The term article of manufacture includes a computer program, carrier, or media accessible from any computer-readable storage device. For example, computer-readable storage media include magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips, etc.), optical disks (e.g., CDs, DVDs, etc.), smart cards, and flash. Includes, but is not limited to, memory devices (e.g., EEPROM, cards, sticks, key drives, etc.). Additionally, various storage media presented herein include one or more devices and/or other machine-readable media for storing information.

It is to be understood that the specific order or hierarchy of steps in the processes presented is an example of illustrative approaches. It is to be understood that the specific order or hierarchy of steps in processes may be rearranged within the scope of the present disclosure, based on design priorities. The appended method claims present elements of the various steps in a sample order but are not meant to be limited to the particular order or hierarchy presented.

The description of the presented embodiments is provided to enable any person skilled in the art to use or practice the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Accordingly, the disclosure is not limited to the embodiments presented herein, but is to be construed in the broadest scope consistent with the principles and novel features presented herein.

Claims (9)

In the system:
server;
medical staff terminal; and
Includes a reception terminal,
Said server:
processor;
Memory; and
Includes a communication module,
The memory contains instructions for causing the processor to perform the following diagnostic steps, which include:
Upon receiving animal patient data from the medical staff terminal, selecting chart data matching the animal patient data and transmitting the chart data to the medical staff terminal; and
Upon receiving a user input for chart input from the medical staff terminal, updating the chart data,
The chart data includes at least one of the name of the veterinarian in charge, animal information, diagnosis history information, prescription history information, and treatment history information,
The memory includes instructions for causing the processor to perform the following acceptance steps, wherein the acceptance steps include:
Receiving the animal patient data and reception data from the reception terminal, and selecting the chart data matching the animal patient data;
selecting the medical staff terminal based on the chart data and the reception data;
Transmitting certain data of the medical staff terminal to the reception terminal; and
Upon receiving a user input for selecting the certain data from the reception terminal, transmitting the animal patient data and the reception data to the medical staff terminal,
The reception data includes at least one of information on the animal patient's symptoms, information on the animal patient's weight change, information on the animal patient's visit time, and the name of the veterinarian designated by the animal patient's guardian,
The memory is:
Learning data including at least one of data on the species of the animal, data on the age of the animal, data on the sex of the animal, data on medical history, diagnosis data, number of re-examinations for each condition, and number of terminations for each condition. An artificial intelligence model trained to receive data on the disease and data on the animal as input and output at least one veterinarian's name is stored,
The above submission steps are:
In selecting the medical staff terminal, inputting the animal patient data and the reception data into the artificial intelligence model;
Identifying at least one second medical staff terminal according to the output of the artificial intelligence model; and
Comprising the step of selecting the medical staff terminal based on information about the visit time of the animal patient and schedule data of each of the second medical staff terminals,
The above submission steps are:
In identifying a second medical staff terminal, based on the output of the artificial intelligence model, identifying a primary rank of at least one first veterinarian matching at least one of the animal patient data and the reception data;
Among the first veterinarians, if at least one second veterinarian is identified that matches the animal patient data for a critical period, a first weight proportional to the number of matches to the animal patient data for the critical period is assigned to the second veterinarian. Calculating a secondary ranking of the first veterinarian by applying to the primary ranking of;
Among the first veterinarians, if at least one third veterinarian matching the reception data for the critical period is identified, calculating a second weight proportional to the number of times the third veterinarian's treatment data is generated accumulated for the critical period. step;
Calculating a third weight that is proportional to the number of times the third veterinarian's medical care data is generated accumulated outside of the critical period, but has a proportional value smaller than the proportional value of the second weight;
Applying the second weight and the third weight to the second ranking of the third veterinarian to calculate the third ranking of the first veterinarian; and
Based on the tertiary ranking of the first veterinarian, identifying the second medical staff terminal of each fourth veterinarian located within a certain ranking,
Said server:
Transmitting the UI (User Interface) of the application to the medical staff terminal,
The UI is:
a1 area where animal patient information is displayed;
Area a2 where the patient diagnosis chart, which is the diagnosis history of the animal patient, is displayed;
A3 area to record the contents and findings of the questionnaire;
Area a4, which records the disease and diagnosis of animal patients;
A5 area records veterinary prescriptions and tests based on the animal patient's condition, performs them directly, or requests the recorded information;
Area a6, which is a request button for sending guidance data, care guide, and is an entry button for sending guidance data to the guardian terminal; and
This is an area that manages the diagnosis history of animal patients and includes area a7 where the history of multiple diagnosis data is displayed,
Said server:
Data matching the keywords entered in the a4 area above include the Korean name for the disease, the English name for the disease, the code connection point that refers to the disease in the EMR, an explanation to help understand the disease, and information on general treatment methods for the disease. Provide an explanation of important items on a previously registered disease notice, including guardian's performance guidelines for managing the disease and precautions for managing the disease, to the medical staff terminal through the application,
The a4 area is:
a4-1, which is a check box that displays the disease system classification and diagnosis name for each condition, and checks the confirmation status for each condition;
a4-2, a check box to check the closure status;
a4-3, a check box for checking whether to return for a second visit; and
Includes a button to display the veterinarian who performed the diagnosis and receive input for deleting the record for each condition,
The a7 area is:
Among the diagnostic data constituting the chart data, it includes a7-1, which is a button to display only diagnostic data that is not checked for a4-2,
The UI is:
When each tag displayed in the a7 area is selected, the animal patient's medical treatment data related to the keyword indicated in the tag is searched and a results window for the search results is displayed,
The a7 area is:
When any one diagnostic data is selected, a4-3 is matched and displayed for each diagnostic data;
Displaying a review record window, including a review start button for obtaining an input entering the a4 area,
system. According to paragraph 1,
The diagnostic steps are:
In updating the chart data, receiving at least one diagnosis for a condition from the medical staff terminal;
Based on the chart data, determining whether to reexamine the diagnosis;
If it is determined that this is the first diagnosis for the diagnosis, a user input for selecting at least one of a check button for confirmation of the diagnosis and a check button for termination of the disease, and information on the diagnostician, a veterinarian who made the diagnosis, Receiving diagnostic data; and
Based on the diagnosis data, updating the history of the diagnosis name in the chart data,
The diagnostic data includes at least one of disease information, test information, symptom information, prescription information, and information on the diagnostician,
system. According to paragraph 2,
The diagnostic steps are:
If it is determined that the diagnosis is a repeat diagnosis, selecting at least one second diagnosis data included in the unfinished medical treatment history that matches the same diagnosis based on the chart data;
identifying a re-examination session for the diagnosis based on the second diagnosis data; and
Comprising the step of transmitting the second diagnosis data, the name of the veterinarian in charge matched to the second diagnosis data, and visit history data for the visit round to the medical staff terminal,
system. According to paragraph 3,
The diagnostic steps are:
When receiving a user input for selecting at least one second condition matching the visit history data from the medical staff terminal, selecting third diagnosis data matching the second condition from among the second diagnosis data; and
Including transmitting the third diagnostic data to the medical staff terminal,
system. According to paragraph 3,
The diagnostic steps are:
In updating the history, if it is determined that the diagnosis is a repeat diagnosis, matching and storing the number of times the diagnosis occurred again;
Based on the diagnostic data, if the diagnosis is identified as confirmed, storing the diagnosis as a confirmed diagnosis, and if the diagnosis is not identified as confirmed, storing the diagnosis as a probable diagnosis; and
Based on the diagnostic data, if the condition is identified as being terminated, classifying the diagnosis as a condition for which treatment has been completed,
system. delete According to paragraph 1,
The memory includes instructions for causing the processor to perform the following schedule management steps, which include:
When the chart data is updated, identifying reservation data based on the updated chart data;
Based on the reservation data, identifying at least one reservation item among a reservation for a visit, a reservation for hospitalization, and a call reservation; and
Comprising the step of updating the schedule data based on the reservation item,
system. delete delete